Biology subjects

Hehnly, C.

Publications and source records attributed to Hehnly, C..

3 recordsLinked to original sources

bioRxiv2022

Type IV pili is a critical virulence factor in clinical isolates of Paenibacillus thiaminolyticus

Hydrocephalus, the leading indication for childhood neurosurgery worldwide, is particularly prevalent in low-and-middle-income countries (LMICs). Hydrocephalus preceded by an infection, or postinfectious hydrocephalus (PIH), accounts for up to 60% of hydrocephalus in LMICs. Since many children with hydrocephalus suffer poor long-term outcomes despite surgical intervention, prevention of hydrocephalus remains paramount. Our previous studies implicated a novel bacterial pathogen, Paenibacillus thiaminolyticus, as a contributor to PIH in Uganda. Here we report the isolation of three P. thiaminolyticus strains, Mbale, Mbale2, and Mbale3, from patients with PIH and the demonstration that the three clinical isolates exhibit virulence in mice while P. thiaminolyticus type strain, B-4156, does not. We constructed complete genome assemblies of the clinical isolates as well as the reference strain and performed comparative genomics and proteomics analyses to identify potential virulence factors. One candidate virulence factor is a cluster of genes carried on a mobile genetic element that encodes a type IV pilus and is present in all three PIH patient strains but absent in the type strain. Proteomic and transcriptomic data confirmed the expression of this cluster of genes in the Mbale strain, while CRISPR-mediated deletion of the gene cluster substantially reduced the virulence of this strain. Our comparative proteogenomic analysis also identified various antibiotic resistance loci in the virulent strains. These results provide insight into the mechanism of virulence of Paenibacillus thiaminolyticus and suggest avenues for the diagnosis and treatment of this novel bacterial pathogen. Author SummaryPostinfectious hydrocephalus (PIH), a devastating sequela of neonatal infection, is associated with increased childhood mortality and morbidity. Paenibacillus thiaminolyticus was recently identified as the dominant organism highly associated with PIH in an African cohort. Our whole-genome sequencing, RNA sequencing and proteomics of three clinical isolates and a type strain in combination with CRISPR editing has revealed the type IV pili (T4P), encoded in a mobile genetic element, as a critical virulence factor for P. thiaminolyticus infection. Given the widespread presence of T4P in pathogens, the presence of T4P operon could serve as an important diagnostic and therapeutic target in P. thiaminolyticus and related bacteria.

microbiology↗

bioRxiv2021

Differential richness inference for 16S rRNA marker gene surveys

Individual and environmental health outcomes are frequently linked to changes in the diversity of associated microbial communities. This makes deriving health indicators based on microbiome diversity measures essential. While microbiome data generated using high throughput 16S rRNA marker gene surveys are appealing for this purpose, 16S surveys also generate a plethora of spurious microbial taxa. When this artificial inflation in the observed number of taxa (i.e., richness, a diversity measure) is ignored, we find that changes in the abundance of detected taxa confound current methods for inferring differences in richness. Here we argue that the evidence of our own experiments, theory guided exploratory data analyses and existing literature, support the conclusion that most sub-genus discoveries are spurious artifacts of clustering 16S sequencing reads. We proceed based on this finding to model a 16S surveys systematic patterns of sub-genus taxa generation as a function of genus abundance to derive a robust control for false taxa accumulation. Such controls unlock classical regression approaches for highly flexible differential richness inference at various levels of the surveyed microbial assemblage: from sample groups to specific taxa collections. The proposed methodology for differential richness inference is available through an R package, Prokounter. Package availability: https://github.com/mskb01/prokounter

bioinformatics↗

bioRxiv2020

Vaginal Microbiome Topic Modelling of Laboring Ugandan Women With and Without Fever

The composition of the maternal vaginal microbiome may influence the duration of pregnancy, onset of labor and even neonatal outcomes. Maternal microbiome research in sub Saharan-Africa has focused on non-pregnant and postpartum composition of the vaginal microbiome. We examined the vaginal microbiome composition of 99 laboring Ugandan women using routine microbiology and 16S ribosomal DNA sequencing from two hypervariable regions (V1-V2 and V3-V4), using standard hierarchical methods. We then introduce Grades of Membership (GoM) modeling for the vaginal microbiome, a method often used in the text mining machine learning literature. Leveraging GoM models, we create a basis composed of a small number of microbial topics whose linear combination optimally represents each patient yielding more accurate associations. We identified relationships between defined communities and the presentation or absence of intrapartum fever. Using a random forest model we showed that by including novel microbial topic models we improved upon clinical variables to predict maternal fever. We also show by integrating clinical variables with a microbial topic model into this model found young maternal age, fever report earlier in the current pregnancy, and longer labors, as well as a more diverse, less Lactobacillus dominated microbiome were features of labor associated with intrapartum fever. These results better define relationships between presentation or absence of intrapartum fever, demographics, peripartum course, and vaginal microbial communities, and improve our understanding of the impact of the microbiome on maternal and neonatal infection risk.

genomics↗